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Population density and spatial pattern of sclerotia of
Sclerotinia sclerotiorum in desert lettuce production
fields
a
Periasamy Chitrampalam & Barry M. Pryor
a
a
Division of Plant Pathology and Microbiology, Department of Plant Sciences, University of
Arizona, Tucson, AZ, 85721, USA
Accepted author version posted online: 30 Sep 2013.Published online: 10 Oct 2013.
To cite this article: Periasamy Chitrampalam & Barry M. Pryor , Canadian Journal of Plant Pathology (2013): Population
density and spatial pattern of sclerotia of Sclerotinia sclerotiorum in desert lettuce production fields , Canadian Journal of
Plant Pathology, DOI: 10.1080/07060661.2013.841758
To link to this article: http://dx.doi.org/10.1080/07060661.2013.841758
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Can. J. Plant Pathol., 2013
http://dx.doi.org/10.1080/07060661.2013.841758
Soilborne pathogens/Agents pathogènes telluriques
Population density and spatial pattern of sclerotia of Sclerotinia
sclerotiorum in desert lettuce production fields
PERIASAMY CHITRAMPALAM AND BARRY M. PRYOR
Downloaded by [University of Arizona] at 12:13 11 October 2013
Division of Plant Pathology and Microbiology, Department of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
(Accepted 2 September 2013)
Abstract: Soil population densities and spatial patterns of sclerotia produced by Sclerotinia sclerotiorum were determined in six commercial
lettuce production fields with varying histories of lettuce drop in Yuma County, AZ. Each field was divided into eight approximate equal
sections and in each section, a plot (10 × 20 m) was randomly selected for soil sampling. Soil cores were collected along both diagonals at
2 m intervals in each plot and sclerotia populations were determined by wet sieving. The average soil sclerotia population per plot ranged from
0.0 to 5.8/100 g soil. The highest and the lowest percent of individual soil samples with ≥ 1 sclerotia/100 g soil per plot were 63% and 7%,
respectively. Three indices of dispersions – variance/mean, Morisita’s index and Lloyd’s index – calculated for each of the six fields indicated
that sclerotia distributions were aggregated. However, in none of the fields could the sclerotia distributions be adequately described by the
Poisson, negative binomial or Neyman type A distributions.
Keywords: lettuce drop, sampling strategy, sclerotia distribution
Résumé: Les densités des populations vivant dans le sol et les profils spatiaux des sclérotes produits par Sclerotinia sclerotiorum ont été
déterminés dans six champs d’Yuma County, en Arizona, où l’on produit commercialement de la laitue et dans lesquels l’historique de la
pourriture sclérotique de la laitue diffère. Chaque champ a été divisé en huit sections à peu près égales et, dans chaque section, une parcelle
(10 m × 20 m) a été choisie aléatoirement en vue d’en échantillonner le sol. Les carottes de sol ont été prélevées dans chaque parcelle, à tous
les 2 m, sur les deux diagonales, et les populations de sclérotes ont été identifiées par criblage par voie humide. La population moyenne de
sclérotes par parcelle variait de 0,0 à 5,8/100 g de sol. Le pourcentage le plus élevé d’échantillons de sol affichant un sclérote ou plus par
100 g de sol par parcelle était de 63% et le plus bas, de 7%. Trois indices de dispersion – moyenne et variance, indice de Morisita et indice de
Lloyd – , calculés pour chacun des six champs, ont indiqué que les distributions de sclérotes étaient agrégatives. Toutefois, les distributions de
sclérotes n’ont pu être adéquatement décrites dans aucun des champs par la courbe de Poisson, par distribution binomiale négative ou par
distribution de Neyman type A.
Mots clés: distribution des sclérotes, pourriture sclérotique de la laitue, stratégie d’échantillonnage
Introduction
Lettuce drop is one of the most destructive diseases of
lettuce (Lactuca sativa L.) and has been reported in all
lettuce-growing regions of the world (Dillard & Grogan,
1985; Subbarao, 1998). In the USA, the disease regularly occurs in the two primary lettuce-producing states
Correspondence to: Barry M. Pryor. E-mail: bmpryor@u.arizona.edu
© 2013 The Canadian Phytopathological Society
of Arizona and California. Yield losses vary from 1% to
nearly 75% depending on conditions, but under ideal disease conditions an entire field may be lost (Purdy, 1979;
Subbarao, 1998). The disease is caused by two closely
related soilborne fungi, Sclerotinia sclerotiorum (Lib.) de
Bary and S. minor Jagger. Although both fungi are present
Downloaded by [University of Arizona] at 12:13 11 October 2013
P. Chitrampalam and B. M. Pryor
in the lettuce-growing areas of Arizona and California,
their distribution is somewhat distinct. In the cooler region
of coastal California, S. minor is the predominant species.
However, in the desert production areas of Yuma Co,
Arizona, and Imperial Co, California, which are quite distinctive from other western production areas in regard
to soil and climate, S. sclerotiorum is the predominant
species (Subbarao, 1998).
Both fungi produce sclerotia, masses of hyphae surrounded by a tough melanin layer, that serve as both
survival structures and primary inoculum for subsequent
lettuce crops. Sclerotia of S. minor infect the host directly
by producing mycelium. However, sclerotia of S. sclerotiorum can infect the host either directly by producing
mycelium or indirectly by producing apothecia and subsequently ascospores (Subbarao et al., 1994; Chitrampalam
et al., 2008). In desert production areas of Arizona and
California, the specific conditions required to prime the
sclerotia to produce apothecia are not commonly encountered and thus, the disease is primarily initiated by
myceliogenic germination of sclerotia (Subbarao, 1998;
Matheron & Porchas, 2004).
Sclerotia of S. sclerotiorum can survive up to
seven years and their longevity is affected by location
of sclerotia within the soil profile, duration of burial and
soil temperature and moisture (Subbarao et al., 1994;
Matheron, & Porchas, 2005). Sclerotia at depths greater
than 10 cm have reduced viability and are generally not
capable of causing disease due to unfavourable O2 and
CO2 levels, low soil temperature, high soil moisture,
and colonization of sclerotia by antagonistic microorganisms (Grogan et al., 1980; Imolehin & Grogan, 1980;
Subbarao, 1998). In contrast, sclerotia within 8 cm of the
soil surface and 2 cm of the lettuce taproot have high rates
of successful infection (Subbarao et al., 1994).
Commercially acceptable cultivars with adequate levels of resistance are not currently available. Thus, current
management strategies for lettuce drop rely primarily
on fungicides such as iprodione and boscalid. However,
the level of disease management achieved with fungicides is not dramatic and is also inconsistent (Matheron
& Porchas, 2005; Chitrampalam et al., 2008). A greater
reduction in disease may be achieved with an integrated disease management approach, which includes an
increased focus on reducing sclerotia populations in the
soil.
To effectively assess the impact of soilborne sclerotia
on lettuce drop and assess the impact of management
strategies on sclerotial populations, estimates of soilborne sclerotia populations need to be available. For
effective sclerotia sampling and reliable density estimations to be possible, preliminary information regarding
2
densities and distribution in commercial fields are needed.
In previous studies on soil sclerotial distribution for various soilborne fungi, including Macrophomina phaseolina
(Tassi) Goid., Verticillium dahlia Kleb. and Sclerotinia
minor (Smith & Rowe, 1984; Dillard & Grogan, 1985;
Mihail & Alcorn, 1987), results revealed that soilborne
sclerotia exhibited aggregated spatial distributions to
varying degrees depending on differences in ecology
among fungal species. However, no such studies have
been conducted for S. sclerotiorum. Although work by
Hao & Subbarao (2003) investigated mean soil populations of sclerotia in California fields and the associated
aggregated pattern of disease incidence, that study did
not describe the underlying soil distribution patterns of
sclerotia. This deficiency in descriptive data is even more
acute in regard to the unique desert production areas of
the southwestern USA and its effect on the ecology of S.
sclerotiorum.
Sampling for soilborne pathogens usually involves collecting soil samples at intervals along one of several
pre-determined paths through a field such as an X, W
or diagonal pattern (Lin et al., 1979; Nicot et al., 1984).
Alternatively, sampling sites can be selected by using simple random sampling, stratified random sampling, cluster
sampling or other survey sampling techniques (Mihail
& Alcorn, 1987). Sampling methods (random vs. cluster sampling) become more important than sampling size
when disease is aggregated. In previous studies, sampling along X-shaped paths covering a smaller demarcated
area within the field provided information about the area
for both random and aggregated pathogen populations in
computer-simulated fields (Lin et al., 1979). The same
study also suggested that where the population is aggregated, samples should be taken from multiple areas across
the entire field.
The objective of this study was to determine soil population densities of sclerotia of S. sclerotiorum in the prime
winter lettuce production areas around Yuma, AZ, in fields
with varied histories of disease incidences. Spatial patterns of sclerotia in soil were established along with mean
aggregate size for those populations determined to have a
clumped distribution. These data are required for the subsequent development of general soil sampling strategies
necessary for improved lettuce drop disease management
in desert agroecosystems.
Materials and methods
Field sampling
Six lettuce fields of approximately 8 hectares, each with a
history of lettuce drop, were selected for sampling. All
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Sclerotinia sclerotiorum population density
fields were located in the prime winter lettuce production area around Yuma, AZ, and were regularly cropped
to lettuce using conventional lettuce production practices
for the area. The selection of fields was assisted by the
University of Arizona Vegetable Extension Specialist, Dr.
Mike Matheron, who was familiar with all fields in question. Fields A, B and C had severe outbreaks of lettuce
drop in the previous season, estimated at > 50% disease
incidence. Fields D, E and F had moderate levels of lettuce drop, estimated at 20–30%. The soil and climatic
conditions were similar across this sampling area and all
fields had been recently harvested and disc harrowed to
incorporate crop residue.
The sampling strategy suggested by Lin et al. (1979) for
aggregated distributions was used with minor modification for this study. To determine the sclerotia distribution
pattern in different parts of the field, each field was
divided into eight approximate equal parts and one plot
(10 × 20 m) was randomly selected in each part for sampling. In each plot, 24 soil cores were collected across
both diagonals at 2 m intervals by inserting a 2.65 cmdiameter soil auger to a depth of 7 cm. Each soil sample
was placed in individual paper bags with plot and diagonal position recorded and returned to the laboratory. Thus,
a total of 192 samples were collected from each field.
Sclerotium population density determination
Soil samples were air dried in paper bags at room temperature and stored until analysis. Immediately prior to
analysis, each sample was homogenized and mixed thoroughly. From each sample, 100 g of soil was wet sieved
through a US Std. series # 18 (The W. S. Tyler Company,
Ohio, USA) and the recovered sclerotia were enumerated by examination under a stereo microscope at 60×
(Subbarao et al., 1994). For each plot, descriptive statistics such as mean, variance and range for sclerotia/100 g
soil were calculated. The sampling data from all plots of
each field were then combined and analysed field-wise
both by individual soil cores values (192 soil cores) and by
plot means (8 plot means). Analysis of variance was performed on mean sclerotia of different fields to check for
significance differences in the mean population among lettuce fields (Sigmastat Software Inc., San Jose, California,
USA).
Analysis of spatial pattern of sclerotia in soil
Three indices of dispersion; the variance to mean ratio,
Morisita’s index of dispersion, and Lloyd’s index of
patchiness (Mihail & Alcorn, 1987), were calculated for
3
each plot by sample (n = 24) and for each field both by
plot (n = 8) and by sample (n = 192) to test for deviation
from unity (Lin et al., 1979). Morisita’s index of dispersion was calculated by using the following formula: Id=n
[((x2 ) – x)/((x) 2 – x)], where n is number of sampling units and × is the number of sclerotia per sampling
unit (Mihail & Alcorn, 1987). Lloyd’s index of patchiness
was calculated using the following formula: LIP = X∗ /X
where X∗ is the mean crowding and X is the mean population (Shukla et al., 1985). Mean crowding (X∗ ) was
calculated by X∗ = X ((S2 /X )–1) where X is the
mean and S2 is the variance (Lloyd, 1967). Values that are
significantly greater than 1 indicate an aggregated spatial
pattern (Southwood, 1978). Significant departure of index
of dispersion from 1.0 was tested using the chi-square test
statistic (Ludwig & Reynolds, 1988).
The spatial pattern within plots and the effect of
varying the size/interval of the sampling units (the distance between the two sampling points) on the detection of underlying spatial patterns were analysed using
Hill’s two-term local quadrat variance method (TTLQV)
(Ludwig & Reynolds, 1988). Data gathered from a series
of contiguous sites in each diagonal across plots were
grouped into different blocks by adding together adjacent sampling site data, and variance for these blocks was
calculated as follows:
Var1 (X) = (1/n − 1) (x1 − x2 )2 /2 + (x2 − x3 )2 /2)
+ . . . . . . . + (xn − 1 − xn)2 /2)], and
Var2 (X) = (1/n − 3) (x1 + x2 − x3 − x4 )2 /4
+ (x2 + x3 − x4 − x5 )2 /4) + . . . . . . .]
where Var1 (X) = variance of counts at block size 1,
Var2 (X) = variance of counts at block size 2, n = number
of quadrats (sampling units), x1 = number of organisms
counted in sampling unit 1, and so on. The precision of
sampling size used in this study to estimate the sclerotial
population was determined by using the following formula (Southwood, 1978), n = (s/Ex) 2 , where n is
the number of samples required, s = standard deviation, ×= mean, and E is the predetermined standard error
(20% of the mean which is an acceptable error in most
studies of this kind) (Elliot, 1971).
The Poisson, Neyman type A and negative binomial
discrete frequency distributions were fit to the dataset
from each field by using the PADIS statistical program
(Lopez & Velazquez, 1997). This program assesses the
P. Chitrampalam and B. M. Pryor
4
degree to which the dataset was described by the particular theoretical distribution by using a chi-square goodness
of fit technique. An agreement with Poisson would indicate a random spatial pattern and an agreement with the
negative binomial or Neyman type A distribution would
indicate an aggregate distribution (Mihail & Alcorn,
1987).
Downloaded by [University of Arizona] at 12:13 11 October 2013
Determination of sclerotia viability
To determine the potential of each sclerotium collected
from the field to cause disease, viability of sclerotia was
ascertained for all the collected sclerotia from three of
the six lettuce fields. Sclerotia were surface sterilized in
10% household bleach for 1 minute and washed twice
with sterilized water. Each sclerotium was individually
placed on a 2% water agar plug (1 cm diam) in a Petri
plate and incubated at 20 ◦ C for a week. The per cent
sclerotia germination (viability) was calculated for each
field.
Results
Sclerotia population density determination
The number of sclerotia of S. sclerotiorum per 100 g of
soil from lettuce production fields ranged from 0 to 42
(Table 1). More than 80% of the samples from fields D,
E and F did not contain any sclerotia (Fig. 1). Field C
and field E contained the minimum (36%) and maximum
number (93%) of samples with no sclerotia, respectively.
Field C had the highest percentage of samples (20%)
with more than 5 sclerotia per 100 g of soil. The mean
number of sclerotia per 100 g of soil for individual fields
Table 1. Descriptive statistics for sclerotia populations of
Sclerotinia sclerotiorum in six lettuce fields.
Indices of dispersiona
Field
A
B
C
D
E
F
Rangea
Meana
Variance
V/M
Morisita’s
Index
Lloyd’s
Index
0–35
0–42
0–24
0–11
0–4
0–8
1.2
2.9
2.9
0.27
0.08
0.36
54.6
51.1
18.8
1.00
0.13
1.09
8.9∗
17.7∗
6.4∗
3.66∗
1.63∗
3.06∗
8.9∗
6.8∗
2.9∗
10.81∗
9.17∗
6.85∗
7.9∗
16.7∗
5.4∗
2.66∗
0.63
2.06∗
The statistics were performed for each field using the sclerotia data from
composite samples (192).
a Sclerotia/100 g of soil.
Values followed by an asterisk (∗ ) are significantly greater than 1.0 at
P ≤ 0.05, indicating an aggregated distribution. V/M = Variance/Mean.
The detailed statistics for each plot per field are given in the supplement
Table.
ranged from 0.08 to 2.9. Fields B and C had the highest
mean number of sclerotia (2.9 sclerotia/100 g of soil)
and field E had the lowest mean number of sclerotia
(0.08 sclerotia/100 g soil).
Analysis of spatial pattern of sclerotia in soil
When indices of dispersion were calculated per plot, all
three indices indicated that sclerotia were aggregated in
all plots in fields B and C (Table S1). In field A, an aggregated distribution was indicated by all three indices in
five plots, by two indices in one plot, and by one index
in one plot. However, in one of the eight plots in field
A, an aggregate distribution was not supported by any of
the three indices. In fields D, E and F, at least one of the
three indices of dispersion indicated an aggregate distribution in three, one and five plots, respectively. When the
indices of dispersion were calculated per field using data
from individual soil cores (n = 192), all indices indicated
aggregated distributions in fields A, B and C. However,
when the indices were calculated per field using mean data
from each plot (n = 8), no indices indicated aggregated
distributions, revealing a uniformity in mean plot sclerotia
population across each field (Table S1). For fields D, E
and F, most indices indicated aggregated distributions of
sclerotia when the indices were calculated per field using
individual soil core data (n = 192). Once again, when the
indices were calculated per field using mean data from
each plot, no indices indicated aggregated distributions in
fields D and F. However, in field E, the Morisita’s index
indicated an aggregated distribution (Table S1).
The analysis of spatial pattern within each plot by
two term local quadrat (TTLQ) method revealed that
sclerotial distribution was aggregated along 46% of the
diagonals from all fields combined (Table 2 and Fig. 2).
Aggregate sizes calculated by TTLQ analysis ranged from
2 to 12 metres in diameter (Table 2). The number of
sampling units (soil cores) required to estimate the field
sclerotia populations with an allowable sampling error of
20% of the mean was 178, 152 and 55 for field A, B and
C, respectively, which is below the number of sampling
units (n = 192) used in this study (Table 3). However,
the number of sampling units required to estimate the
field sclerotia populations within allowable sampling error
were 334, 499 and 214 for fields D, E and F, respectively,
which were higher than the number of sampling units used
in this study (Table 3). When estimations of field populations were based upon plot means, the number of plots
required to estimate field populations was higher than the
number of plots used in this study in five of six lettuce
fields (Table 3).
Sclerotinia sclerotiorum population density
5
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Fig. 1. Frequency distribution of sclerotia densities of Sclerotinia sclerotiorum in six lettuce fields.
Table 2. Distribution patterns of sclerotia of S. sclerotiorum
within two diagonals of the same plots of six lettuce fields.
Variance peak (radius of population aggregate)a
at least one of the theoretical distribution model (Table
S2). None of the plots in field E had enough sclerotia frequency to run a goodness of fit to any of three theoretical
distribution models (Table S2).
Plot
1
2
3
4
5
6
7
8
Field d1 d2 d1 d2 d1 d2 d1 d2 d1 d2 d1 d2 d1 d2 d1 d2
A
B
C
D
E
F
1 1
4 R
6 U
3 U
− −
R U
3
4
2
R
2
2
R
U
U
U
2
−
4
6
2
1
2
4
U
U
6
2
U
6
4 R 4 U
6 1 4 R
6 R 6 4
2 U − −
− − − 4
U 4 R 4
4
5
6
R
1
4
2 1
U 1
U 4
− R
− −
U −
R
6
R
1
R
4
1
1
4
6
−
4
U
U
R
4
R
4
Determination of sclerotia viability
All sclerotia recovered from soil samples of fields D,
E and F, which totalled 57, 17 and 74, respectively,
were tested for viability. All sclerotia (100%) regenerated
Sclerotinia colonies in seven days of incubation and thus
were considered viable.
a Radius
of population aggregate (in metres) was obtained by plotting the
variance of different blocks calculated using TTLQV method against block
sizes. d1 and d2 are the two diagonal paths of each plot. R = variance
fluctuates randomly with the different block sizes which indicates random
distribution, U = variance is low and does not fluctuate at different block
sizes which indicates uniform distribution, – = no sclerotia recovered from
the diagonal.
The test for goodness of fit of observed sclerotial distributions to theoretical distribution models indicated that
the sclerotial distributions were not adequately described
by any of three distribution models tested; Poisson,
negative binomial and Neyman Type A distributions
(Table 4). However, analysis by plot within each field indicated that the sclerotial distributions for all plots in fields
A, B and C, except plot 7 in field B, fit to at least one of
three theoretical distribution models (Table S2). Two plots
from field A best fit to the Poisson distribution model. The
other plots in fields A, B and C best fit to either negative binomial, Neyman type A or both distribution models.
In fields D and F, only three and five plots, respectively,
had sufficient sclerotia frequency to run goodness of fit
tests to fit theoretical distribution models. However, only
two plots from field D and four plots from field F fit to
Discussion
The mean sclerotia populations of S. sclerotiorum in the
six lettuce field selected for this study located near Yuma,
AZ, and with a prior history of lettuce drop, ranged from
0.08 to 2.9 sclerotia/100 g of soil. The only other comparative data from lettuce fields comes from previous work
by Hao & Subbarao (2005), which provided estimates of
the sclerotia population of S. sclerotiorum in nine lettuce
fields in the San Joaquin Valley, CA. In that work, the
sclerotial population averaged 0.06 sclerotia/100 cm3 of
soil. Several factors could have contributed to the higher
sclerotial populations in this study compared with the
study by Hao & Subbarao (2005) such as fungicide use
or method of irrigation, both of which are known to significantly impact the incidence of lettuce drop (Subbarao,
1998). However, one factor that likely contributed more
substantially is the intensive lettuce cropping system used
in the desert production areas around Yuma, AZ, as
compared with the San Joaquin Valley. In desert lettuce
production systems, the higher value of the winter lettuce
crop and a more limited availability of land suitable for
P. Chitrampalam and B. M. Pryor
6
Table 4. Goodness of fit of the distribution of sclerotia of
Sclerotinia sclerotiorum in six lettuce fields to statistical distribution.
χ 2 value
Field
No. of samples
used
Poissona
Negative
binomiala
Neyman
type Aa
192
192
192
192
192
192
93.3∗
77.0∗
12.7∗
7.1∗
x
9.1∗
89.2∗
33.4∗
18.9∗
19.7∗
x
10.7∗
444.0∗
16.8∗
852.0∗
170.3∗
5.9∗
83.3∗
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A
B
C
D
E
F
a Chi square value. Asterisk (∗ ) indicates chi square statistic was highly significant (P < 0.01) and that the composite soil core frequency data was
not adequately described by the corresponding frequency distribution. x
indicates that the frequency of sclerotia was not enough to calculate a χ 2 .
Goodness of fit was also performed separately for sclerotia data from each
plot per field, and the results are listed in supplement table.
Fig. 2. Graph of variance peaks for random, uniform and clumped
patterns of sclerotia of Sclerotinia sclerotiorum from two diagonals
of the same plot for representative plots from field A (A), field B
(B) and field C (C) lettuce fields.
lettuce production encourages continuous lettuce production and discourages winter crop rotation, which would
likely contribute to a build-up of inoculum over time.
Table 3.
Field
A
B
C
D
E
F
When rotation is practiced, selection of alternate crops
would likely play a role in differential soil sclerotia populations as well. For example, crop rotation with a non-host
crop such as broccoli significantly reduced soil populations of sclerotia of S. sclerotiorum in the Salinas Valley,
CA, where broccoli rotation is commonly used (Hao &
Subbarao, 2003). Crop rotation with broccoli and other
non-host crops is common in San Joaquin Valley lettuce
production as well. However, in the Yuma area, crops
such as cauliflower, cabbage and celery, which are also
susceptible to S. sclerotiorum, are occasionally rotated
with lettuce and this likely can contribute to the higher
populations of sclerotia found in these soils.
Sclerotial populations in fields A, B and C were more
than 10 times higher than that in fields D, E and F.
Complete histories of the six lettuce fields regarding
prior disease problems or cultural practices were not
available, so the reason for the higher level of sclerotia
population in the first three fields could not be determined. However, disease incidences for each sampled
field immediately prior to harvest and the period of
soil sampling were approximated by the extension specialist who helped in selecting the fields for this study
A precision of sampling size used in estimating sclerotia populations of Sclerotinia sclerotiorum in six lettuce fields.
No. of soil
samples taken
No. of soil samples
required with 20% SE
Sampling error with
192 samples (%)
No. of plots
sampled
No. of plots required
with 20% SE
Sampling error
with 8 plots (%)
192
192
192
192
192
192
178
152
55
334
499
214
19
18
10
25
31
20
8
8
8
8
8
8
15
10
3
32
21
9
27
22
10
40
33
22
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Sclerotinia sclerotiorum population density
(Dr. Mike Matheron). Considering what is known about
lettuce drop epidemiology, whereby each infected head
results in the proliferation of sclerotia that function as
inoculum in subsequent crops (Subbarao, 1998), the
higher end-of-season incidence of disease estimated in
fields A, B and C compared with fields D, E and F
would explain some of the differences in post-harvest
sclerotia population observed between fields. This study
did not determine the impact of the estimated soil sclerotia
densities on disease incidence in the subsequent lettuce
crops in each of the sampled fields. However, a previous study did establish the relationship between sclerotia
densities and lettuce drop incidence for all three major
lettuce types commonly grown in the desert production
areas: crisphead, romaine and leaf lettuces (Chitrampalam
et al., 2010). Therefore, using the estimated numbers of
sclerotia in soil from the sampling strategy established
in this study, and the relationship between soil sclerotia
populations and subsequent incidence of lettuce drop
established in the previous study, one could predict the
potential disease incidence in a prospective production
field.
The distribution of sclerotia of S. sclerotiorum in soil
was non-random in all six lettuce fields and the high
variance-to-mean ratios indicated an aggregated distribution of sclerotia, similar to that of several other soilborne
sclerotia-forming fungi (Smith & Rowe, 1984; Mihail
& Alcorn, 1987). Morisita’s index of dispersion, Lloyd
index of patchiness and the two-term local quadrat variance method also suggested an aggregated distribution.
In a few plots, a random or uniform distribution pattern
was observed along the plot diagonals, but this was due
to sclerotial counts of zero in most of the sampling units
of those particular diagonals. The consistent aggregated
pattern of sclerotia of S. sclerotiorum, where ascospores
are rarely produced in desert environments, was similar to
that of the closely related S. minor, which rarely produces
ascospores (Dillard & Grogan, 1985). Indeed, the indices
of dispersion obtained for S. sclerotiorum in this study
(1.15 to 29.6) were higher than that obtained for other
sclerotia-forming soilborne fungi such as S. minor (1.6 to
2.9) and M. phaseolina (1.52 to 6.19) (Dillard & Grogan,
1985; Mihail & Alcorn, 1987). One reason for the higher
indices of dispersion for S. sclerotiorum could be that S.
minor and M. phaseolina usually produce large numbers
of small sclerotia, in contrast to lower numbers of large
sclerotia by S. sclerotiorum, and these may be more easily dispersed from the site of origin, thereby reducing the
size of aggregate. Moreover, M. phaseolina also produces
asexual conidia regularly in addition to sclerotia which
could also potentially influence the size of aggregate by
spreading the pathogen more widely.
7
Lettuce fields are usually disked soon after crop harvest, and lettuce residues containing large numbers of
recently formed sclerotia are incorporated and concentrated in the area immediately surrounding the previously
infected lettuce head. This contributes to an aggregated
pattern of recoverable sclerotia in the following season.
The incidence of lettuce drop from mycelial infection
shows a similar aggregated pattern (Dillard & Grogan,
1985; Hao & Subbarao, 2005). Interestingly, studies have
shown that the incidence of lettuce drop due to ascospore
infection has an aggregated pattern as well, suggesting
that ascospore dispersal in lettuce fields is also localized
(Hao & Subbarao, 2005).
Analysis of soil sclerotia population across fields
(n = 6) for goodness of fit to theoretical distribution models showed that the observed sclerotia distribution in each
field was not adequately described by either Poisson, negative binomial or Neyman type A models, even though
indices of dispersal suggested an aggregated distribution.
A similar failure of fitting of observed distribution to the
theoretical distribution models was also observed with
microsclerotia populations of Macrophomina phaseolina
collected from cultivated soils in Arizona where the calculated indices distributions also indicated an aggregated
distribution (Mihail & Alcorn, 1987). However, analysis
of soil population data across plots (n = 24) revealed
that sclerotia distributions in most plots were adequately
described by either negative binomial or Neyman type
A models, representing aggregated distribution patterns,
and in agreement with the indices of dispersal. The available theoretical distribution models representing aggregated distributions are perhaps not optimal for describing sclerotia of Sclerotinia and Macrophomina in soil
and new distribution models may be required to more
accurately represent their distribution in cultivated field
soils.
The precision of sample size used in this study to estimate sclerotia population was tested using a 20% standard
error as suggested by Southwood (1978). Based upon
data from individual soil cores, the predicted sample size
required to attain this level of precision was lower for
fields A, B and C than the sample size used in this study
(n = 192). However, the sample size required in determining the sclerotia population for fields D, E and F was
higher than the sample size used in this study. The reason
for the low number of soil samples required to determine
sclerotia population in fields from A to C was due to the
presence of sclerotia in a higher percentage of sampling
units and all of the eight plots in all three fields had mean
sclerotia populations between 0.5 to 5.8/100 g of soil. The
standard error calculated with 192 soil samples for fields
A, B and C (10, 18 and 19%, respectively) was lower than
Downloaded by [University of Arizona] at 12:13 11 October 2013
P. Chitrampalam and B. M. Pryor
the allowable standard error (20%). However, the standard
error calculated for fields D, E and F (25, 31 and 20%,
respectively) were equal to or higher than the allowable
standard error. The reason for higher requirement of sampling units and high standard error in fields D and E was
due to the presence of low sclerotia population in these
two fields. Since the number of soil samples required to
determine sclerotia population for most fields was equal
to or below the sample size used in this study, a sample
size of 192 cores is a reasonable sized sampling to determine sclerotia population in fields which have a history
of high incidence of lettuce drop. For fields with a lower
incidence of lettuce drop, this sampling size may not be
sufficient for precision. However, if the disease potential
is not as high, a less precise estimation of soil population
may be acceptable.
The calculated potential sampling error based upon
plot means was higher than the allowable sampling error
(20%) in five out of six fields sampled (22 to 40%),
although the sampling error in fields A, B and F (27,
22 and 22%, respectively) was very close to the allowable
sampling error. To achieve a sampling error of 20% would
require 15, 10 and 9 plots for fields A, B and F, respectively. Note that almost doubling the number of plots for
field A (8 plots to 15 plots) only reduced the standard error
by 7. Thus, the sample size of 8 plots used in this study to
estimate sclerotia population appears to be reasonable for
a field with high incidence of lettuce drop. Again, if the
disease potential is not high, a less precise estimation of
soil population may be acceptable.
In summary, the sclerotia populations of S. sclerotiorum in winter lettuce production fields in the deserts of
Arizona were higher than that reported in other areas and
followed an aggregated distribution. The number of sampling units used in this study was sufficient to determine
the observed sclerotia population within a reasonable
sampling error and thus these data can be utilized as
foundations for subsequent studies on the ecology and
management S. sclerotiorum in desert agroecosystems.
Although this study estimated the sclerotia population of
S. sclerotiorum and determined their distribution in lettuce fields, it did not assess the potential impact of this
inoculum on subsequent lettuce production. Thus, a future
study on the relationship between sclerotium density and
disease in desert winter production will be critical for
the future development of more effective management
strategies.
Acknowledgements
This work was supported in part by the University
of Arizona College of Agriculture and Life Sciences,
8
the Arizona Iceberg Lettuce Research Council and the
Arizona Department of Agriculture. We would like to
thank Monica Alvarado and Chad Cox for assistance in
collecting and processing the field soil samples.
Supplemental data
Supplemental data for this article can be accessed here:
http://dx.doi.org/10.1080/07060661.2013.841758
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